DOE Awards $3.7M for National Lab HPC Research for Energy Spplications

As part of DOE’s High Performance Computing for Energy Innovation (HPC4EI) initiative, the 13 selected teams will work with the DOE’s national laboratories to apply advanced modeling, simulation, and data analysis to projects that improve manufacturing efficiency and explore new materials for energy applications.

Selected projects will use HPC to address complex challenges, from improving additive manufacturing processes to increasing the lifecycle energy efficiency of jet-engine components to improving the performance of materials used to convert CO₂ into high-value chemicals and products.

HPC4EI is the umbrella initiative for DOE’s HPC for Manufacturing (HPC4Mfg) and HPC for Materials in Applied Energy Technologies (HPC4Materials) programs.

High Performance Computing for Manufacturing (HPC4Mfg) projects are:

• Raytheon Technologies Research Center. Robust Film Cooling Under Manufacturing Uncertainty for Improved Jet Engine LifeCycle Energy Efficiency. DOE award: $300,000
  Raytheon Technologies Research Center and Argonne National Laboratory will use HPC to develop a physics-informed machine learning technique to desensitize film cooling effectiveness to manufacturing variability and to inform design practitioners of the impact of manufacturing uncertainties on the lifecycle energy efficiency of gas turbine engines.
• Polyceed Inc. (dba Glass Dyenamics). HPC- and Machine-Learning-Based Modelling of Electrochromic Dyes for High Performance and Reduced-Cost Manufacturability of Electrochromic (EC) Devices. DOE award: $300,000
  Polyceed Inc. (dba Glass Dyenamics) and Oak Ridge National Laboratory will use HPC- and Machine-Learning-Based Modelling to develop new electrochromic dyes for smart glass building windows with improved roll-to-roll manufacturability and low-cost.
• 3M Company. Next Generation Nonwovens Manufacturing Based on Model-Driven Simulation Machine Learning Approach. DOE award: $297,000
  3M Company in partnership with Argonne National Laboratory will use a combination of HPC-based CFD simulations and a machine learning to minimize energy consumption of melt blown (MB) fiber manufacturing processes. Such processes are widely used for 3M products including filters, fabrics and insulation materials.
• Element 16 Technologies, Inc. High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage. DOE award: $300,000
  Element 16 Technologies, Inc. and National Renewable Energy Laboratory will use HPC to improve Element 16’s molten sulfur TES product design with a high-fidelity HPC model validated by experimental data.
• The Procter & Gamble Co. Reinventing the Green Consumer Products Landscape with Material and Process Design using High Performance Computing. DOE award: $300,000
  The Procter & Gamble Co. and Sandia National Laboratories will use HPC to create an eco-system of HPC-enabled fiber manufacturing models to allow for defect-free production of solvent-free detergents with an accelerated timescale and reduced waste streams compared to traditional approaches such as build-test cycles.
• Electric Power Research Institute, Inc. Modeling Dynamic Stress-Strain-Temperature Profiles in Induction Pipe Bending to Improve Productivity and Avoid Cracking in Energy Intensive Applications. DOE award: $300,000
  Electric Power Research Institute, Inc. and Argonne National Laboratory will use HPC to apply state-of-the-art modeling and simulation tools to induction pipe bending nickel-based alloys for energy applications.
• Generon IGS. Modeling of Shell-Side Gas Membrane Modules to Optimize Counter-Currency and Improve Selective Gas Permeation. DOE award: $300,000
  Generon IGS and Oak Ridge National Laboratory will use HPC to model the flow patterns in a shell-side fed gas separation module to maximize counter current flow patterns which could lead to a 50% reduction in the methane lost through the CO₂ removal process.
• General Motors LLC. Improving Additive Manufactured Component Performance through Multi-Scale Microstructure Simulation and Process Optimization. DOE award: $300,000
  General Motors LLC and Oak Ridge National Laboratory will use HPC to develop a high-performance lightweight additive manufacturing (AM) engine piston through material, shape and process optimization.
• Commonwealth Center for Advanced Manufacturing. Integrated Process and Materials Modeling for Development of Additive Manufacturing of Refractory Materials for Critical Applications. DOE award: $300,000
  Commonwealth Center for Advanced Manufacturing and Oak Ridge National Laboratory will use HPC to establish foundational knowledge for developing and implementing technologies that enable the use of directed energy deposition (DED) for additively producing large gas turbine components using refractory metals.
• Praxair Surface Technologies. Optimization of Processing Parameters for Metal Powder Production by Gas Atomization Utilizing CFD Simulations. DOE award: $150,000
  Praxair Surface Technologies and Ames Laboratory will use HPC to improve quality and yield of metal powder for additive manufacturing produced via close-coupled gas atomization.

HPC for Materials in Applied Energy Technologies (HPC4Materials) projects are:

• Raytheon Technologies Research Center. An ICME Modeling Framework for Metal Matrix Composites (MMC) Focusing on Ultrahigh Temperature Matrix Material and Tungsten Carbide Reinforcement Particulate. DOE award: $300,000
  Raytheon Technologies Research Center and Argonne National Laboratory will use HPC to design and fabricate ultra-high temperature metal matrix composite in order to obtain as-desired microstructure, strength, fracture toughness, creep resistance and oxidation resistance at operating temperature > 1850 ˚F to 2250 ˚F for enabling cost-effective performance improvement in aerospace applications.
• Advanced Manufacturing LLC. Development of Hierarchical ODS High Entropy Alloys under Guidance of ICME. DOE award: $300,000
  Advanced Manufacturing LLC and National Energy Technology Laboratory will use HPC to develop and manufacture cost-effective, oxide dispersion-strengthened (ODS), NiCrFeCo-rich high entropy alloys (HEAs) that are superior to Ni-based superalloys (e.g. IN740) for repair or replacement service in extreme environments.
• Opus 12 Inc. Transport Analysis and Optimization in a MW-Scale CO₂ Electrolyzer. DOE award: $300,000
  Opus 12 and Lawrence Livermore National Laboratory will use HPC to better understand the heat distribution within the electrolyzer and optimize the flow field design for efficient heat removal in order to minimize cooling costs which decrease energy efficiency. The project output will inform the design of Opus 12’s first-of-a-kind MW-scale electrolyzer development, capable of converting over one ton per day of CO₂ into valuable products.

HPC4Mfg is funded by DOE’s Office of Energy Efficiency and Renewable Energy’s Advanced Manufacturing Office. DOE’s Office of Fossil Energy and Carbon Management will fund the project selections in HPC4Materials.